library(ggplot2)
library(gganimate)
library(animation)
library(tweenr)You data should include at least 4 coloumns:
A variable of interest (e.g., accuracy scores), which will be the y-axis
A variable representing time (e.g., trial number), which will be the x-axis
A varaible representing individual data points (e.g., participant number)
A variable representing condition to which individuals are assigned (e.g., male vs. female)
data <- read.csv("animated_plot_data.csv")
head(data,30) # show the first 30 rows of the data frame## Trial.Number Participant Condition Accuracy
## 1 1 1 Female 11
## 2 1 2 Female 13
## 3 1 3 Female 6
## 4 1 4 Female 17
## 5 1 5 Female 2
## 6 1 6 Female 7
## 7 1 7 Male 11
## 8 1 8 Male 34
## 9 1 9 Male 11
## 10 1 10 Male 27
## 11 1 11 Male 6
## 12 1 12 Male 14
## 13 2 1 Female 46
## 14 2 2 Female 16
## 15 2 3 Female 13
## 16 2 4 Female 25
## 17 2 5 Female 8
## 18 2 6 Female 26
## 19 2 7 Male 26
## 20 2 8 Male 4
## 21 2 9 Male 13
## 22 2 10 Male 32
## 23 2 11 Male 33
## 24 2 12 Male 14
## 25 3 1 Female 59
## 26 3 2 Female 32
## 27 3 3 Female 28
## 28 3 4 Female 41
## 29 3 5 Female 16
## 30 3 6 Female 25Then, use the tweenr package to make a smooth transition between each time point.
The “tween_elements functions will create two additional coloums to your data frame:”.frame" (corresponding to the origina trial number) and “.group” (corresponding to the original participant number).
data$ease <- "linear" #add a coloumn to the data frame
data2<- tween_elements(data, 'Trial.Number', 'Participant', 'ease', nframes = 100) # create 100 frames between each trial number
head(data2,30) # show the first 30 rows of the data frame## Trial.Number Condition Accuracy .frame .group
## 1 1.000000 Female 11.000000 0 1
## 910 1.000000 Male 27.000000 0 10
## 1011 1.000000 Male 6.000000 0 11
## 1112 1.000000 Male 14.000000 0 12
## 102 1.000000 Female 13.000000 0 2
## 203 1.000000 Female 6.000000 0 3
## 304 1.000000 Female 17.000000 0 4
## 405 1.000000 Female 2.000000 0 5
## 506 1.000000 Female 7.000000 0 6
## 607 1.000000 Male 11.000000 0 7
## 708 1.000000 Male 34.000000 0 8
## 809 1.000000 Male 11.000000 0 9
## 2 1.166667 Female 16.833334 1 1
## 911 1.166667 Male 27.833333 1 10
## 1012 1.166667 Male 10.500000 1 11
## 1113 1.166667 Male 14.000000 1 12
## 103 1.166667 Female 13.500000 1 2
## 204 1.166667 Female 7.166667 1 3
## 305 1.166667 Female 18.333333 1 4
## 406 1.166667 Female 3.000000 1 5
## 507 1.166667 Female 10.166667 1 6
## 608 1.166667 Male 13.500000 1 7
## 709 1.166667 Male 29.000000 1 8
## 810 1.166667 Male 11.333333 1 9
## 3 1.333333 Female 22.666667 2 1
## 912 1.333333 Male 28.666667 2 10
## 1013 1.333333 Male 15.000000 2 11
## 1114 1.333333 Male 14.000000 2 12
## 104 1.333333 Female 14.000000 2 2
## 205 1.333333 Female 8.333333 2 3Now, we’ll create our wanted plot using ggplot.
plot<- ggplot(data=data2, aes(x = Trial.Number, y = Accuracy, group=.group, color=Condition, frame=.frame, cumulative=TRUE))+
geom_line(lwd=1, alpha=0.8)+ #change line trasparency with alpha = x
scale_x_continuous("Trial Number", breaks=c(1:17))+
scale_y_continuous("Accuracy")+
theme_classic()+
theme(text = element_text(size = 25), axis.text.x = element_text(size=20), legend.position=c(.8,.2))And finally, let’s animate the plot and save it!
# change the speed of the animation by chanding interval = x
gganimate(plot, interval = 0.05)## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?# remove the title by frame by adding title_frame = FALSE
gganimate(plot, title_frame = FALSE,filename="animated_plot.gif",ani.height=500, ani.width=700, interval = 0.05) # save as gif## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?## Output at: animated_plot.gif